query_sift

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states the purpose without revealing traits such as idempotency, side effects, error conditions, or authorization needs. This is a significant gap for a query tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: one sentence for purpose followed by a clear Args list. Every element is essential, and the purpose is front-loaded. No extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and zero schema coverage, the description covers basic usage and parameters adequately. However, it lacks behavioral context (e.g., whether the query is read-only) and does not address potential errors or limitations, which is moderate incompleteness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description adds meaningful parameter explanations: 'sift_id: The sift identifier' and 'natural_language: The question to answer' with an example query. This compensates well, though more detail on expected format or constraints could further help.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the action 'Run a natural language query' and the resource 'sift's extracted records', which distinguishes it from siblings like aggregate_sift (aggregation) and find_records (different query method). The verb is specific and the resource is well-defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for natural language queries on sift records but does not explicitly contrast with sibling tools or provide when-to-use/when-not-to-use guidance. No alternatives are mentioned, leaving the agent to infer based on tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.